Selection of motion vector precision

ABSTRACT

Approaches to selection of motion vector (“MV”) precision during video encoding are presented. These approaches can facilitate compression that is effective in terms of rate-distortion performance and/or computational efficiency. For example, a video encoder determines an MV precision for a unit of video from among multiple MV precisions, which include one or more fractional-sample MV precisions and integer-sample MV precision. The video encoder can identify a set of MV values having a fractional-sample MV precision, then select the MV precision for the unit based at least in part on prevalence of MV values (within the set) having a fractional part of zero. Or, the video encoder can perform rate-distortion analysis, where the rate-distortion analysis is biased towards the integer-sample MV precision. Or, the video encoder can collect information about the video and select the MV precision for the unit based at least in part on the collected information.

RELATED APPLICATION INFORMATION

The present application claims the benefit of U.S. Provisional PatentApplication No. 61/925,090, filed Jan. 8, 2014, the disclosure of whichis hereby incorporated by reference. The present application also claimsthe benefit of U.S. Provisional Patent Application No. 61/934,574, filedJan. 31, 2014, the disclosure of which is hereby incorporated byreference.

BACKGROUND

Engineers use compression (also called source coding or source encoding)to reduce the bit rate of digital video. Compression decreases the costof storing and transmitting video information by converting theinformation into a lower bit rate form. Decompression (also calleddecoding) reconstructs a version of the original information from thecompressed form. A “codec” is an encoder/decoder system.

Over the last two decades, various video codec standards have beenadopted, including the ITU-T H.261, H.262 (MPEG-2 or ISO/IEC 13818-2),H.263 and H.264 (MPEG-4 AVC or ISO/IEC 14496-10) standards, the MPEG-1(ISO/IEC 11172-2) and MPEG-4 Visual (ISO/IEC 14496-2) standards, and theSMPTE 421M (VC-1) standard. More recently, the HEVC standard (ITU-TH.265 or ISO/IEC 23008-2) has been approved. Extensions to the HEVCstandard (e.g., for scalable video coding/decoding, for coding/decodingof video with higher fidelity in terms of sample bit depth or chromasampling rate, or for multi-view coding/decoding) are currently underdevelopment. A video codec standard typically defines options for thesyntax of an encoded video bitstream, detailing parameters in thebitstream when particular features are used in encoding and decoding. Inmany cases, a video codec standard also provides details about thedecoding operations a decoder should perform to achieve conformingresults in decoding. Aside from codec standards, various proprietarycodec formats define other options for the syntax of an encoded videobitstream and corresponding decoding operations.

In general, video compression techniques include “intra-picture”compression and “inter-picture” compression. Intra-picture compressiontechniques compress individual pictures, and inter-picture compressiontechniques compress pictures with reference to a preceding and/orfollowing picture (often called a reference or anchor picture) orpictures.

Inter-picture compression techniques often use motion estimation andmotion compensation to reduce bit rate by exploiting temporal redundancyin a video sequence. Motion estimation is a process for estimatingmotion between pictures. In one common technique, an encoder usingmotion estimation attempts to match a current block of sample values ina current picture with a candidate block of the same size in a searcharea in another picture, the reference picture. When the encoder findsan exact or “close enough” match in the search area in the referencepicture, the encoder parameterizes the change in position between thecurrent and candidate blocks as motion data (such as a motion vector(“MV”)). An MV is conventionally a two-dimensional value, having ahorizontal MV component that indicates left or right spatialdisplacement and a vertical MV component that indicates up or downspatial displacement. In general, motion compensation is a process ofreconstructing pictures from reference picture(s) using motion data.

An MV can indicate a spatial displacement in terms of an integer numberof sample grid positions starting from a co-located position in areference picture for a current block. For example, for a current blockat position (32, 16) in a current picture, the MV (−3, 1) indicatesposition (29, 17) in the reference picture. Or, an MV can indicate aspatial displacement in terms of a fractional number of sample gridpositions from a co-located position in a reference picture for acurrent block. For example, for a current block at position (32, 16) ina current picture, the MV (−3.5, 1.25) indicates position (28.5, 17.25)in the reference picture. To determine sample values at fractionaloffsets in the reference picture, the encoder typically interpolatesbetween sample values at integer-sample positions. Such interpolationcan be computationally intensive. During motion compensation, a decoderalso performs the interpolation as needed to compute sample values atfractional offsets in reference pictures.

Different video codec standards and formats have used MVs with differentMV precisions. For integer-sample MV precision, an MV componentindicates an integer number of sample grid positions for spatialdisplacement. For a fractional-sample MV precision such as ½-sample MVprecision or ¼-sample MV precision, an MV component can indicate aninteger number of sample grid positions or fractional number of samplegrid positions for spatial displacement. For example, if the MVprecision is ¼-sample MV precision, an MV component can indicate aspatial displacement of 0 samples, 0.25 samples, 0.5 samples, 0.75samples, 1.0 samples, 1.25 samples, and so on. Some video codecstandards and formats support switching of MV precision during encoding.Encoder-side decisions about which MV precision to use are not madeeffectively, however, in certain encoding scenarios.

SUMMARY

In summary, the detailed description presents innovations inencoder-side operations for selection of motion vector (“MV”) precision.For example, when a video encoder encodes video, the video encoderdetermines an MV precision for a unit of the video.

According to one aspect of the innovations described herein, when itdetermines the MV precision for the unit, the video encoder can identifya set of MV values having a fractional-sample MV precision. The videoencoder can select the MV precision for the unit based at least in parton prevalence, within the set of MV values, of MV values having afractional part of zero.

According to another aspect of the innovations described herein, when itdetermines the MV precision for the unit, the video encoder can performrate-distortion analysis to decide between multiple MV precisions, whichinclude one or more fractional-sample MV precisions and integer-sampleMV precision. The rate-distortion analysis is biased towards theinteger-sample MV precision by: (a) scaling a distortion cost, (b)adding a penalty to the distortion cost, (c) scaling a bit rate cost,(d) adding a penalty to the bit rate cost, and/or (e) adjusting aLagrangian multiplier factor.

According to another aspect of the innovations described herein, when itdetermines the MV precision for the unit, the video encoder can collectinformation about the video and select the MV precision for the unit,from among multiple MV precisions, based at least in part on thecollected information. The multiple MV precisions include one or morefractional-sample MV precisions and integer-sample MV precision.

The innovations for encoder-side options for selection of MV precisioncan be implemented as part of a method, as part of a computing deviceadapted to perform the method or as part of a tangible computer-readablemedia storing computer-executable instructions for causing a computingdevice to perform the method. The various innovations can be used incombination or separately.

The foregoing and other objects, features, and advantages of theinvention will become more apparent from the following detaileddescription, which proceeds with reference to the accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of an example computing system in which somedescribed embodiments can be implemented.

FIGS. 2a and 2b are diagrams of example network environments in whichsome described embodiments can be implemented.

FIG. 3 is a diagram of an example encoder system in conjunction withwhich some described embodiments can be implemented.

FIGS. 4a and 4b are diagrams illustrating an example video encoder inconjunction with which some described embodiments can be implemented.

FIG. 5 is diagram illustrating a computer desktop environment withcontent that may provide input for screen capture.

FIG. 6 is a diagram illustrating mixed-content video with natural videocontent and artificial video content.

FIGS. 7a and 7b are diagrams illustrating motion compensation with MVvalues having an integer-sample spatial displacement andfractional-sample spatial displacement, respectively.

FIG. 8 is a flowchart illustrating a generalized technique for adaptingMV precision during encoding.

FIG. 9 is a flowchart illustrating an example technique for adapting MVprecision during encoding using a low-complexity approach.

FIG. 10 is a diagram illustrating different regions of a pictureaccording to some variations of the low-complexity approach.

DETAILED DESCRIPTION

The detailed description presents innovations in the selection of motionvector (“MV”) precision during encoding. These approaches can facilitatecompression that is effective in terms of rate-distortion performanceand/or computational efficiency. For example, a video encoder determinesan MV precision for a unit of video from among multiple MV precisions,which include one or more fractional-sample MV precisions andinteger-sample MV precision. The video encoder can identify a set of MVvalues having a fractional-sample MV precision, then select the MVprecision for the unit based at least in part on prevalence of MV values(within the set) having a fractional part of zero. Or, the video encodercan perform rate-distortion analysis, where the rate-distortion analysisis biased towards the integer-sample MV precision. Or, the video encodercan collect information about the video and select the MV precision forthe unit based at least in part on the collected information. Or, thevideo encoder can determine the MV precision for a unit of video in someother way.

Although operations described herein are in places described as beingperformed by a video encoder, in many cases the operations can beperformed by another type of media processing tool.

Some of the innovations described herein are illustrated with referenceto syntax elements and operations specific to the HEVC standard. Theinnovations described herein can also be implemented for other standardsor formats.

More generally, various alternatives to the examples described hereinare possible. For example, some of the methods described herein can bealtered by changing the ordering of the method acts described, bysplitting, repeating, or omitting certain method acts, etc. The variousaspects of the disclosed technology can be used in combination orseparately. Different embodiments use one or more of the describedinnovations. Some of the innovations described herein address one ormore of the problems noted in the background. Typically, a giventechnique/tool does not solve all such problems.

I. Example Computing Systems.

FIG. 1 illustrates a generalized example of a suitable computing system(100) in which several of the described innovations may be implemented.The computing system (100) is not intended to suggest any limitation asto scope of use or functionality, as the innovations may be implementedin various computing systems, including special-purpose computingsystems adapted for video encoding.

With reference to FIG. 1, the computing system (100) includes one ormore processing units (110, 115) and memory (120, 125). The processingunits (110, 115) execute computer-executable instructions. A processingunit can be a central processing unit (“CPU”), processor in anapplication-specific integrated circuit (“ASIC”) or any other type ofprocessor. In a multi-processing system, multiple processing unitsexecute computer-executable instructions to increase processing power.For example, FIG. 1 shows a central processing unit (110) as well as agraphics processing unit or co-processing unit (115). The tangiblememory (120, 125) may be volatile memory (e.g., registers, cache, RAM),non-volatile memory (e.g., ROM, EEPROM, flash memory, etc.), or somecombination of the two, accessible by the processing unit(s). The memory(120, 125) stores software (180) implementing one or more innovationsfor selection of MV precision during encoding, in the form ofcomputer-executable instructions suitable for execution by theprocessing unit(s).

A computing system may have additional features. For example, thecomputing system (100) includes storage (140), one or more input devices(150), one or more output devices (160), and one or more communicationconnections (170). An interconnection mechanism (not shown) such as abus, controller, or network interconnects the components of thecomputing system (100). Typically, operating system software (not shown)provides an operating environment for other software executing in thecomputing system (100), and coordinates activities of the components ofthe computing system (100).

The tangible storage (140) may be removable or non-removable, andincludes magnetic disks, magnetic tapes or cassettes, CD-ROMs, DVDs, orany other medium which can be used to store information and which can beaccessed within the computing system (100). The storage (140) storesinstructions for the software (180) implementing one or more innovationsfor selection of MV precision during encoding.

The input device(s) (150) may be a touch input device such as akeyboard, mouse, pen, or trackball, a voice input device, a scanningdevice, or another device that provides input to the computing system(100). For video, the input device(s) (150) may be a camera, video card,TV tuner card, screen capture module, or similar device that acceptsvideo input in analog or digital form, or a CD-ROM or CD-RW that readsvideo input into the computing system (100). The output device(s) (160)may be a display, printer, speaker, CD-writer, or another device thatprovides output from the computing system (100).

The communication connection(s) (170) enable communication over acommunication medium to another computing entity. The communicationmedium conveys information such as computer-executable instructions,audio or video input or output, or other data in a modulated datasignal. A modulated data signal is a signal that has one or more of itscharacteristics set or changed in such a manner as to encode informationin the signal. By way of example, and not limitation, communicationmedia can use an electrical, optical, RF, or other carrier.

The innovations can be described in the general context ofcomputer-readable media. Computer-readable media are any availabletangible media that can be accessed within a computing environment. Byway of example, and not limitation, with the computing system (100),computer-readable media include memory (120, 125), storage (140), andcombinations of any of the above.

The innovations can be described in the general context ofcomputer-executable instructions, such as those included in programmodules, being executed in a computing system on a target real orvirtual processor. Generally, program modules include routines,programs, libraries, objects, classes, components, data structures, etc.that perform particular tasks or implement particular abstract datatypes. The functionality of the program modules may be combined or splitbetween program modules as desired in various embodiments.Computer-executable instructions for program modules may be executedwithin a local or distributed computing system.

The terms “system” and “device” are used interchangeably herein. Unlessthe context clearly indicates otherwise, neither term implies anylimitation on a type of computing system or computing device. Ingeneral, a computing system or computing device can be local ordistributed, and can include any combination of special-purpose hardwareand/or hardware with software implementing the functionality describedherein.

The disclosed methods can also be implemented using specializedcomputing hardware configured to perform any of the disclosed methods.For example, the disclosed methods can be implemented by an integratedcircuit (e.g., an ASIC such as an ASIC digital signal processor (“DSP”),a graphics processing unit (“GPU”), or a programmable logic device(“PLD”) such as a field programmable gate array (“FPGA”)) speciallydesigned or configured to implement any of the disclosed methods.

For the sake of presentation, the detailed description uses terms like“determine” and “use” to describe computer operations in a computingsystem. These terms are high-level abstractions for operations performedby a computer, and should not be confused with acts performed by a humanbeing. The actual computer operations corresponding to these terms varydepending on implementation. As used herein, the term “optimiz*”(including variations such as optimization and optimizing) refers to achoice among options under a given scope of decision, and does not implythat an optimized choice is the “best” or “optimum” choice for anexpanded scope of decisions.

II. Example Network Environments.

FIGS. 2a and 2b show example network environments (201, 202) thatinclude video encoders (220) and video decoders (270). The encoders(220) and decoders (270) are connected over a network (250) using anappropriate communication protocol. The network (250) can include theInternet or another computer network.

In the network environment (201) shown in FIG. 2a , each real-timecommunication (“RTC”) tool (210) includes both an encoder (220) and adecoder (270) for bidirectional communication. A given encoder (220) canproduce output compliant with a variation or extension of the HEVCstandard (also known as H.265), SMPTE 421M standard, ISO/IEC 14496-10standard (also known as H.264 or AVC), another standard, or aproprietary format, with a corresponding decoder (270) accepting encodeddata from the encoder (220). The bidirectional communication can be partof a video conference, video telephone call, or other two-party ormulti-party communication scenario. Although the network environment(201) in FIG. 2a includes two real-time communication tools (210), thenetwork environment (201) can instead include three or more real-timecommunication tools (210) that participate in multi-party communication.

A real-time communication tool (210) manages encoding by an encoder(220). FIG. 3 shows an example encoder system (300) that can be includedin the real-time communication tool (210). Alternatively, the real-timecommunication tool (210) uses another encoder system. A real-timecommunication tool (210) also manages decoding by a decoder (270).

In the network environment (202) shown in FIG. 2b , an encoding tool(212) includes an encoder (220) that encodes video for delivery tomultiple playback tools (214), which include decoders (270). Theunidirectional communication can be provided for a video surveillancesystem, web camera monitoring system, screen capture module, remotedesktop conferencing presentation or other scenario in which video isencoded and sent from one location to one or more other locations.Although the network environment (202) in FIG. 2b includes two playbacktools (214), the network environment (202) can include more or fewerplayback tools (214). In general, a playback tool (214) communicateswith the encoding tool (212) to determine a stream of video for theplayback tool (214) to receive. The playback tool (214) receives thestream, buffers the received encoded data for an appropriate period, andbegins decoding and playback.

FIG. 3 shows an example encoder system (300) that can be included in theencoding tool (212). Alternatively, the encoding tool (212) uses anotherencoder system. The encoding tool (212) can also include server-sidecontroller logic for managing connections with one or more playbacktools (214). A playback tool (214) can also include client-sidecontroller logic for managing connections with the encoding tool (212).

III. Example Encoder Systems.

FIG. 3 is a block diagram of an example encoder system (300) inconjunction with which some described embodiments may be implemented.The encoder system (300) can be a general-purpose encoding tool capableof operating in any of multiple encoding modes such as a low-latencyencoding mode for real-time communication, a transcoding mode, and ahigher-latency encoding mode for producing media for playback from afile or stream, or it can be a special-purpose encoding tool adapted forone such encoding mode. The encoder system (300) can be implemented asan operating system module, as part of an application library or as astandalone application. Overall, the encoder system (300) receives asequence of source video frames (311) from a video source (310) andproduces encoded data as output to a channel (390). The encoded dataoutput to the channel can include content encoded using a selected MVprecision.

The video source (310) can be a camera, tuner card, storage media,screen capture module, or other digital video source. The video source(310) produces a sequence of video frames at a frame rate of, forexample, 30 frames per second. As used herein, the term “frame”generally refers to source, coded or reconstructed image data. Forprogressive-scan video, a frame is a progressive-scan video frame. Forinterlaced video, in example embodiments, an interlaced video framemight be de-interlaced prior to encoding. Alternatively, twocomplementary interlaced video fields are encoded together as a singlevideo frame or encoded as two separately-encoded fields. Aside fromindicating a progressive-scan video frame or interlaced-scan videoframe, the term “frame” or “picture” can indicate a single non-pairedvideo field, a complementary pair of video fields, a video object planethat represents a video object at a given time, or a region of interestin a larger image. The video object plane or region can be part of alarger image that includes multiple objects or regions of a scene.

An arriving source frame (311) is stored in a source frame temporarymemory storage area (320) that includes multiple frame buffer storageareas (321, 322, . . . , 32 n). A frame buffer (321, 322, etc.) holdsone source frame in the source frame storage area (320). After one ormore of the source frames (311) have been stored in frame buffers (321,322, etc.), a frame selector (330) selects an individual source framefrom the source frame storage area (320). The order in which frames areselected by the frame selector (330) for input to the encoder (340) maydiffer from the order in which the frames are produced by the videosource (310), e.g., the encoding of some frames may be delayed in order,so as to allow some later frames to be encoded first and to thusfacilitate temporally backward prediction. Before the encoder (340), theencoder system (300) can include a pre-processor (not shown) thatperforms pre-processing (e.g., filtering) of the selected frame (331)before encoding. The pre-processing can include color space conversioninto primary (e.g., luma) and secondary (e.g., chroma differences towardred and toward blue) components and resampling processing (e.g., toreduce the spatial resolution of chroma components) for encoding.Typically, before encoding, video has been converted to a color spacesuch as YUV, in which sample values of a luma (Y) component representbrightness or intensity values, and sample values of chroma (U, V)components represent color-difference values. The chroma sample valuesmay be sub-sampled to a lower chroma sampling rate (e.g., for YUV 4:2:0format or YUV 4:2:2), or the chroma sample values may have the sameresolution as the luma sample values (e.g., for YUV 4:4:4 format). InYUV 4:2:0 format, chroma components are downsampled by a factor of twohorizontally and by a factor of two vertically. In YUV 4:2:2 format,chroma components are downsampled by a factor of two horizontally. Or,the video can be encoded in another format (e.g., RGB 4:4:4 format).

The encoder (340) encodes the selected frame (331) to produce a codedframe (341) and also produces memory management control operation(“MMCO”) signals (342) or reference picture set (“RPS”) information. Ifthe current frame is not the first frame that has been encoded, whenperforming its encoding process, the encoder (340) may use one or morepreviously encoded/decoded frames (369) that have been stored in adecoded frame temporary memory storage area (360). Such stored decodedframes (369) are used as reference frames for inter-frame prediction ofthe content of the current source frame (331). The MMCO/RPS information(342) indicates to a decoder which reconstructed frames may be used asreference frames, and hence should be stored in a frame storage area.

Generally, the encoder (340) includes multiple encoding modules thatperform encoding tasks such as partitioning into tiles, intra predictionestimation and prediction, motion estimation and compensation, frequencytransforms, quantization and entropy coding. The exact operationsperformed by the encoder (340) can vary depending on compression format.The format of the output encoded data can be a variation or extension ofHEVC format (H.265), Windows Media Video format, VC-1 format, MPEG-xformat (e.g., MPEG-1, MPEG-2, or MPEG-4), H.26x format (e.g., H.261,H.262, H.263, H.264), or another format.

The encoder (340) can partition a frame into multiple tiles of the samesize or different sizes. For example, the encoder (340) splits the framealong tile rows and tile columns that, with frame boundaries, definehorizontal and vertical boundaries of tiles within the frame, where eachtile is a rectangular region. Tiles are often used to provide optionsfor parallel processing. A frame can also be organized as one or moreslices, where a slice can be an entire frame or region of the frame. Aslice can be decoded independently of other slices in a frame, whichimproves error resilience. The content of a slice or tile is furtherpartitioned into blocks or other sets of samples for purposes ofencoding and decoding.

For syntax according to the HEVC standard, the encoder splits thecontent of a frame (or slice or tile) into coding tree units. A codingtree unit (“CTU”) includes luma sample values organized as a luma codingtree block (“CTB”) and corresponding chroma sample values organized astwo chroma CTBs. The size of a CTU (and its CTBs) is selected by theencoder. A luma CTB can contain, for example, 64×64, 32×32 or 16×16 lumasample values. A CTU includes one or more coding units. A coding unit(“CU”) has a luma coding block (“CB”) and two corresponding chroma CBs.For example, a CTU with a 64×64 luma CTB and two 64×64 chroma CTBs (YUV4:4:4 format) can be split into four CUs, with each CU including a 32×32luma CB and two 32×32 chroma CBs, and with each CU possibly being splitfurther into smaller CUs. Or, as another example, a CTU with a 64×64luma CTB and two 32×32 chroma CTBs (YUV 4:2:0 format) can be split intofour CUs, with each CU including a 32×32 luma CB and two 16×16 chromaCBs, and with each CU possibly being split further into smaller CUs. Thesmallest allowable size of CU (e.g., 8×8, 16×16) can be signaled in thebitstream.

Generally, a CU has a prediction mode such as inter or intra. A CUincludes one or more prediction units for purposes of signaling ofprediction information (such as prediction mode details, displacementvalues, etc.) and/or prediction processing. A prediction unit (“PU”) hasa luma prediction block (“PB”) and two chroma PBs. For anintra-predicted CU, the PU has the same size as the CU, unless the CUhas the smallest size (e.g., 8×8). In that case, the CU can be splitinto four smaller PUs (e.g., each 4×4 if the smallest CU size is 8×8) orthe PU can have the smallest CU size, as indicated by a syntax elementfor the CU. A CU also has one or more transform units for purposes ofresidual coding/decoding, where a transform unit (“TU”) has a lumatransform block (“TB”) and two chroma TBs. A PU in an intra-predicted CUmay contain a single TU (equal in size to the PU) or multiple TUs. Theencoder decides how to partition video into CTUs, CUs, PUs, TUs, etc. Inthe context of the H.264/AVC standard, the term “macroblock” indicates ablock-shaped region similar to that of a CTU for the H.265/HEVCstandard, and the term “sub-macroblock partition” indicates ablock-shaped region similar to that of a CU or PU. As used herein, theterm “block” can indicate a CB, PB, TB, CTU, CU, PU, TU, macroblock,sub-macroblock partition or other set of sample values, depending oncontext.

Returning to FIG. 3, the encoder represents an intra-coded block of asource frame (331) in terms of prediction from other, previouslyreconstructed sample values in the frame (331). For intra block copy(“BC”) prediction, an intra-picture estimator estimates displacement ofa block with respect to the other, previously reconstructed samplevalues. An intra-frame prediction reference region (or intra-predictionregion, for short) is a region of samples in the frame that are used togenerate BC-prediction values for the block. The intra-frame predictionregion can be indicated with a block vector (“BY”) value (determined inBV estimation). For intra spatial prediction for a block, theintra-picture estimator estimates extrapolation of the neighboringreconstructed sample values into the block. The intra-picture estimatorcan output prediction information (such as BV values for intra BCprediction or prediction mode (direction) for intra spatial prediction),which is entropy coded. An intra-frame prediction predictor applies theprediction information to determine intra prediction values.

The encoder (340) represents an inter-frame coded, predicted block of asource frame (331) in terms of prediction from reference frames. Amotion estimator estimates the motion of the block with respect to oneor more reference frames (369). The motion estimator can select a motionvector (“MV”) precision (e.g., integer-sample MV precision, ½-sample MVprecision, or ¼-sample MV precision) as described herein, then use theselected MV precision during motion estimation. When multiple referenceframes are used, the multiple reference frames can be from differenttemporal directions or the same temporal direction. A motion-compensatedprediction reference region is a region of samples in the referenceframe(s) that are used to generate motion-compensated prediction valuesfor a block of samples of a current frame. The motion estimator outputsmotion information such as MV information, which is entropy coded. Amotion compensator applies MV values having the selected MV precision toreference frames (369) to determine motion-compensated prediction valuesfor inter-frame prediction.

The encoder can determine the differences (if any) between a block'sprediction values (intra or inter) and corresponding original values.These prediction residual values are further encoded using a frequencytransform (if the frequency transform is not skipped), quantization andentropy encoding. For example, the encoder (340) sets values forquantization parameter (“QP”) for a picture, tile, slice and/or otherportion of video, and quantizes transform coefficients accordingly. Theentropy coder of the encoder (340) compresses quantized transformcoefficient values as well as certain side information (e.g., MVinformation, selected MV precision, BV values, QP values, modedecisions, parameter choices). Typical entropy coding techniques includeExponential-Golomb coding, Golomb-Rice coding, arithmetic coding,differential coding, Huffman coding, run length coding,variable-length-to-variable-length (“V2V”) coding,variable-length-to-fixed-length (“V2F”) coding, Lempel-Ziv (“LZ”)coding, dictionary coding, probability interval partitioning entropycoding (“PIPE”), and combinations of the above. The entropy coder canuse different coding techniques for different kinds of information, canapply multiple techniques in combination (e.g., by applying Golomb-Ricecoding followed by arithmetic coding), and can choose from amongmultiple code tables within a particular coding technique. In someimplementations, the frequency transform can be skipped. In this case,prediction residual values can be quantized and entropy coded.

An adaptive deblocking filter is included within the motion compensationloop (that is, “in-loop” filtering) in the encoder (340) to smoothdiscontinuities across block boundary rows and/or columns in a decodedframe. Other filtering (such as de-ringing filtering, adaptive loopfiltering (“ALF”), or sample-adaptive offset (“SAO”) filtering; notshown) can alternatively or additionally be applied as in-loop filteringoperations.

The coded frames (341) and MMCO/RPS information (342) (or informationequivalent to the MMCO/RPS information (342), since the dependencies andordering structures for frames are already known at the encoder (340))are processed by a decoding process emulator (350). The decoding processemulator (350) implements some of the functionality of a decoder, forexample, decoding tasks to reconstruct reference frames. In a mannerconsistent with the MMCO/RPS information (342), the decoding processemulator (350) determines whether a given coded frame (341) needs to bereconstructed and stored for use as a reference frame in inter-frameprediction of subsequent frames to be encoded. If a coded frame (341)needs to be stored, the decoding process emulator (350) models thedecoding process that would be conducted by a decoder that receives thecoded frame (341) and produces a corresponding decoded frame (351). Indoing so, when the encoder (340) has used decoded frame(s) (369) thathave been stored in the decoded frame storage area (360), the decodingprocess emulator (350) also uses the decoded frame(s) (369) from thestorage area (360) as part of the decoding process.

The decoded frame temporary memory storage area (360) includes multipleframe buffer storage areas (361, 362, . . . , 36 n). In a mannerconsistent with the MMCO/RPS information (342), the decoding processemulator (350) manages the contents of the storage area (360) in orderto identify any frame buffers (361, 362, etc.) with frames that are nolonger needed by the encoder (340) for use as reference frames. Aftermodeling the decoding process, the decoding process emulator (350)stores a newly decoded frame (351) in a frame buffer (361, 362, etc.)that has been identified in this manner.

The coded frames (341) and MMCO/RPS information (342) are buffered in atemporary coded data area (370). The coded data that is aggregated inthe coded data area (370) contains, as part of the syntax of anelementary coded video bitstream, encoded data for one or more pictures.The coded data that is aggregated in the coded data area (370) can alsoinclude media metadata relating to the coded video data (e.g., as one ormore parameters in one or more supplemental enhancement information(“SEI”) messages or video usability information (“VUI”) messages).

The aggregated data (371) from the temporary coded data area (370) areprocessed by a channel encoder (380). The channel encoder (380) canpacketize and/or multiplex the aggregated data for transmission orstorage as a media stream (e.g., according to a media program stream ortransport stream format such as ITU-T H.222.0 I ISO/IEC 13818-1 or anInternet real-time transport protocol format such as IETF RFC 3550), inwhich case the channel encoder (380) can add syntax elements as part ofthe syntax of the media transmission stream. Or, the channel encoder(380) can organize the aggregated data for storage as a file (e.g.,according to a media container format such as ISO/IEC 14496-12), inwhich case the channel encoder (380) can add syntax elements as part ofthe syntax of the media storage file. Or, more generally, the channelencoder (380) can implement one or more media system multiplexingprotocols or transport protocols, in which case the channel encoder(380) can add syntax elements as part of the syntax of the protocol(s).The channel encoder (380) provides output to a channel (390), whichrepresents storage, a communications connection, or another channel forthe output. The channel encoder (380) or channel (390) may also includeother elements (not shown), e.g., for forward-error correction (“FEC”)encoding and analog signal modulation.

IV. Example Video Encoders.

FIGS. 4a and 4b are a block diagram of a generalized video encoder (400)in conjunction with which some described embodiments may be implemented.The encoder (400) receives a sequence of video pictures including acurrent picture as an input video signal (405) and produces encoded datain a coded video bitstream (495) as output.

The encoder (400) is block-based and uses a block format that depends onimplementation. Blocks may be further sub-divided at different stages,e.g., at the prediction, frequency transform and/or entropy encodingstages. For example, a picture can be divided into 64×64 blocks, 32×32blocks or 16×16 blocks, which can in turn be divided into smaller blocksof sample values for coding and decoding. In implementations of encodingfor the HEVC standard, the encoder partitions a picture into CTUs(CTBs), CUs (CBs), PUs (PBs) and TU (TBs).

The encoder (400) compresses pictures using intra-picture coding and/orinter-picture coding. Many of the components of the encoder (400) areused for both intra-picture coding and inter-picture coding. The exactoperations performed by those components can vary depending on the typeof information being compressed.

A tiling module (410) optionally partitions a picture into multipletiles of the same size or different sizes. For example, the tilingmodule (410) splits the picture along tile rows and tile columns that,with picture boundaries, define horizontal and vertical boundaries oftiles within the picture, where each tile is a rectangular region.

The general encoding control (420) receives pictures for the input videosignal (405) as well as feedback (not shown) from various modules of theencoder (400). Overall, the general encoding control (420) providescontrol signals (not shown) to other modules (such as the tiling module(410), transformer/scaler/quantizer (430), scaler/inverse transformer(435), intra-picture estimator (440), motion estimator (450) andintra/inter switch) to set and change coding parameters during encoding.In particular, in conjunction with the motion estimator (450), thegeneral encoding control (420) can determine MV precision duringencoding. The general encoding control (420) can also evaluateintermediate results during encoding, for example, performingrate-distortion analysis. The general encoding control (420) producesgeneral control data (422) that indicates decisions made duringencoding, so that a corresponding decoder can make consistent decisions.The general control data (422) is provided to the headerformatter/entropy coder (490).

If the current picture is predicted using inter-picture prediction, amotion estimator (450) estimates the motion of blocks of sample valuesof the current picture of the input video signal (405) with respect toone or more reference pictures. The motion estimator (450) can select amotion vector (“MV”) precision (e.g., integer-sample MV precision,½-sample MV precision, or ¼-sample MV precision) as described herein,then use the selected MV precision during motion estimation. The decodedpicture buffer (470) buffers one or more reconstructed previously codedpictures for use as reference pictures. When multiple reference picturesare used, the multiple reference pictures can be from different temporaldirections or the same temporal direction. The motion estimator (450)produces as side information motion data (452) such as MV data, mergemode index values and reference picture selection data, as well as sideinformation that indicates the selected MV precision. The sideinformation including motion data (452) is provided to the headerformatter/entropy coder (490) as well as the motion compensator (455).

The motion compensator (455) applies MV values having the selected MVprecision to the reconstructed reference picture(s) from the decodedpicture buffer (470). When the chroma data for a picture has the sameresolution as the luma data (e.g. when the format is YUV 4:4:4 format orRGB 4:4:4 format), the MV value that is applied for a chroma block maybe the same as the MV value applied for the luma block. On the otherhand, when the chroma data for a picture has reduced resolution relativeto the luma data (e.g. when the format is YUV 4:2:0 format or YUV 4:2:2format), the MV value that is applied for a chroma block may be a MVvalue that has been scaled down and possibly rounded to adjust for thedifference in chroma resolution (e.g., for YUV 4:2:0 format, by dividingthe vertical and horizontal components of the MV value by two andtruncating or rounding them to the precision used for the chroma motioncompensation process; for YUV 4:2:2 format, by dividing the horizontalcomponent of the MV value by two and truncating or rounding it to theprecision used for the chroma motion compensation process). The motioncompensator (455) produces motion-compensated predictions for thecurrent picture.

In a separate path within the encoder (400), an intra-picture estimator(440) determines how to perform intra-picture prediction for blocks ofsample values of a current picture of the input video signal (405). Thecurrent picture can be entirely or partially coded using intra-picturecoding. Using values of a reconstruction (438) of the current picture,for intra spatial prediction, the intra-picture estimator (440)determines how to spatially predict sample values of a current block ofthe current picture from neighboring, previously reconstructed samplevalues of the current picture. Or, for intra BC prediction using BVvalues, the intra-picture estimator (440) estimates displacement of thesample values of the current block to different candidate regions withinthe current picture.

The intra-picture estimator (440) produces as side information intraprediction data (442), such as information indicating whether intraprediction uses spatial prediction or intra BC prediction (e.g., a flagvalue per intra block), prediction mode direction (for intra spatialprediction), and BV values (for intra BC prediction). The intraprediction data (442) is provided to the header formatter/entropy coder(490) as well as the intra-picture predictor (445).

According to the intra prediction data (442), the intra-picturepredictor (445) spatially predicts sample values of a current block ofthe current picture from neighboring, previously reconstructed samplevalues of the current picture. Or, for intra BC prediction, theintra-picture predictor (445) predicts the sample values of the currentblock using previously reconstructed sample values of anintra-prediction region, which is indicated by a BV value for thecurrent block.

The intra/inter switch selects values of a motion-compensated predictionor intra-picture prediction for use as the prediction (458) for a givenblock. When residual coding is not skipped, the difference (if any)between a block of the prediction (458) and a corresponding part of theoriginal current picture of the input video signal (405) provides valuesof the residual (418). During reconstruction of the current picture,when residual values have been encoded/signaled, reconstructed residualvalues are combined with the prediction (458) to produce areconstruction (438) of the original content from the video signal(405). In lossy compression, however, some information is still lostfrom the video signal (405).

In the transformer/scaler/quantizer (430), when a frequency transform isnot skipped, a frequency transformer converts spatial-domain video datainto frequency-domain (i.e., spectral, transform) data. For block-basedvideo coding, the frequency transformer applies a discrete cosinetransform (“DCT”), an integer approximation thereof, or another type offorward block transform (e.g., a discrete sine transform or an integerapproximation thereof) to blocks of prediction residual data (or samplevalue data if the prediction (458) is null), producing blocks offrequency transform coefficients. The encoder (400) may also be able toindicate that such transform step is skipped. The scaler/quantizerscales and quantizes the transform coefficients. For example, thequantizer applies dead-zone scalar quantization to the frequency-domaindata with a quantization step size that varies on a frame-by-framebasis, tile-by-tile basis, slice-by-slice basis, block-by-block basis,frequency-specific basis or other basis. The quantized transformcoefficient data (432) is provided to the header formatter/entropy coder(490). If the frequency transform is skipped, the scaler/quantizer canscale and quantize the blocks of prediction residual data (or samplevalue data if the prediction (458) is null), producing quantized valuesthat are provided to the header formatter/entropy coder (490).

In the scaler/inverse transformer (435), a scaler/inverse quantizerperforms inverse scaling and inverse quantization on the quantizedtransform coefficients. An inverse frequency transformer performs aninverse frequency transform, producing blocks of reconstructedprediction residual values or sample values. If the transform stage hasbeen skipped, the inverse frequency transform is also skipped. In thiscase, the scaler/inverse quantizer can perform inverse scaling andinverse quantization on blocks of prediction residual data (or samplevalue data), producing reconstructed values. When residual values havebeen encoded/signaled, the encoder (400) combines reconstructed residualvalues with values of the prediction (458) (e.g., motion-compensatedprediction values, intra-picture prediction values) to form thereconstruction (438). When residual values have not beenencoded/signaled, the encoder (400) uses the values of the prediction(458) as the reconstruction (438).

For intra-picture prediction, the values of the reconstruction (438) canbe fed back to the intra-picture estimator (440) and intra-picturepredictor (445). Also, the values of the reconstruction (438) can beused for motion-compensated prediction of subsequent pictures. Thevalues of the reconstruction (438) can be further filtered. A filteringcontrol (460) determines how to perform deblock filtering and SAOfiltering on values of the reconstruction (438), for a given picture ofthe video signal (405). The filtering control (460) produces filtercontrol data (462), which is provided to the header formatter/entropycoder (490) and merger/filter(s) (465).

In the merger/filter(s) (465), the encoder (400) merges content fromdifferent tiles into a reconstructed version of the picture. The encoder(400) selectively performs deblock filtering and SAO filtering accordingto the filter control data (462), so as to adaptively smoothdiscontinuities across boundaries in the frames. Other filtering (suchas de-ringing filtering or ALF; not shown) can alternatively oradditionally be applied. Tile boundaries can be selectively filtered ornot filtered at all, depending on settings of the encoder (400), and theencoder (400) may provide syntax within the coded bitstream to indicatewhether or not such filtering was applied. The decoded picture buffer(470) buffers the reconstructed current picture for use in subsequentmotion-compensated prediction.

The header formatter/entropy coder (490) formats and/or entropy codesthe general control data (422), quantized transform coefficient data(432), intra prediction data (442), motion data (452) and filter controldata (462). MV values can be predictively coded. For example, the headerformatter/entropy coder (490) uses Exponential-Golomb coding for entropycoding of various syntax elements such as syntax elements fordifferential MV values, after MV prediction.

The header formatter/entropy coder (490) provides the encoded data inthe coded video bitstream (495). The format of the coded video bitstream(495) can be a variation or extension of HEVC format, Windows MediaVideo format, VC-1 format, MPEG-x format (e.g., MPEG-1, MPEG-2, orMPEG-4), H.26x format (e.g., H.261, H.262, H.263, H.264), or anotherformat.

Depending on implementation and the type of compression desired, modulesof the encoder can be added, omitted, split into multiple modules,combined with other modules, and/or replaced with like modules. Inalternative embodiments, encoders with different modules and/or otherconfigurations of modules perform one or more of the describedtechniques. Specific embodiments of encoders typically use a variationor supplemented version of the encoder (400). The relationships shownbetween modules within the encoder (400) indicate general flows ofinformation in the encoder; other relationships are not shown for thesake of simplicity.

V. Selection of MV Precision During Encoding.

This section presents various approaches to selection of motion vector(“MV”) precision during encoding. These approaches can facilitatecompression that is effective in terms of rate-distortion performanceand/or computational efficiency of encoding and decoding.

The approaches described herein for selecting MV precision can beapplied when encoding any type of video. In particular, however,selection of MV precision as described herein can improve performancewhen encoding certain artificially-created video content such as screencapture content.

A. Types of Video.

In general, screen capture video (also called screen content video orscreen capture content) represents the output of a graphics renderingprocess that generates content for a computer screen or other display.This contrasts with natural video, which refers to video imagerycaptured from a camera sensor view of real-world objects, or videohaving similar characteristics. Screen capture video typically containsrendered text, computer graphics, animation-generated content or othersimilar types of content captured from the output of a rendering processfor a computer display, as opposed to (or in addition to)camera-captured video content only. Common scenarios forencoding/decoding of screen capture content include remote desktopconferencing and encoding/decoding of graphical or text overlays onnatural video or other “mixed content” video. Several of the innovationsdescribed herein are adapted for encoding of screen capture video orother artificially-created video. These innovations can also be used fornatural video, but may not be as effective. Other innovations describedherein are effective in encoding of natural video orartificially-created video.

FIG. 5 shows a computer desktop environment (510) with content that mayprovide input for screen capture. For example, screen capture video canrepresent a series of images of the entire computer desktop (511). Or,screen capture video can represent a series of images for one of thewindows of the computer desktop environment, such as the app window(513) including game content, browser window (512) with Web page contentor window (514) with word processor content.

As computer-generated, artificially-created video content, screencapture content tends to have relatively few discrete sample values,compared to natural video content that is captured using a video camera.For example, a region of screen capture content often includes a singleuniform color, whereas a region in natural video content more likelyincludes colors that gradually vary. Also, screen capture contenttypically includes distinct structures (e.g., graphics, text characters)that are exactly repeated from frame-to-frame, even if the content maybe spatially displaced (e.g., due to scrolling). Screen capture contentis usually encoded in a format (e.g., YUV 4:4:4 or RGB 4:4:4) with highchroma sampling resolution, although it may also be encoded in a formatwith lower chroma sampling resolution (e.g., YUV 4:2:0, YUV 4:2:2).

FIG. 6 shows mixed-content video (620) that includes some natural video(621) and some artificially-created video content. Theartificially-created video content includes a graphic (622) beside thenatural video (621) and a ticker (623) running below the natural video(621). Like the screen capture content shown in FIG. 5, theartificially-created video content shown in FIG. 6 tends to haverelatively few discrete sample values. It also tends to have distinctstructures (e.g., graphics, text characters) that are exactly repeatedfrom frame-to-frame (e.g., due to scrolling).

Screen capture video or mixed-content video can be periodically readfrom an output buffer for a display device, or from one or more otherbuffers storing frames. Or, screen capture video can be provided from ascreen capture module (which may periodically read values from an outputbuffer for a display device, intercept display commands from anoperating system module, or otherwise capture sample values to bedisplayed). Screen capture video or mixed-content video can be from a“live” stream or from a previously recorded stream in storage.

B. Different MV Precisions.

In many encoding scenarios, when encoding screen capture video or otherartificially-created video content, most MV values representinteger-sample spatial displacements, and very few MV values representfractional-sample spatial displacements. This provides opportunities forreducing MV precision to improve overall performance.

FIG. 7a shows motion compensation with an MV (720) having aninteger-sample spatial displacement. The MV (720) indicates a spatialdisplacement of four samples to the left, and one sample up, relative tothe co-located position (710) in a reference picture for a currentblock. For example, for a 4×4 current block at position (64, 96) in acurrent picture, the MV (720) indicates a 4×4 prediction region (730)whose position is (60, 95) in the reference picture. The predictionregion (730) includes reconstructed sample values at integer-samplepositions in the reference picture. An encoder or decoder need notperform interpolation to determine the values of the prediction region(730).

FIG. 7b shows motion compensation with an MV (721) having afractional-sample spatial displacement. The MV (721) indicates a spatialdisplacement of 3.75 samples to the left, and 0.5 samples up, relativeto the co-located position (710) in a reference picture for a currentblock. For example, for a 4×4 current block at position (64, 96) in acurrent picture, the MV (721) indicates a 4×4 prediction region (731)whose position is (60.25, 95.5) in the reference picture. The predictionregion (731) includes interpolated sample values at fractional-samplepositions in the reference picture. An encoder or decoder performsinterpolation to determine the sample values of the prediction region(731). When fractional-sample spatial displacements are allowed, thereare more candidate prediction regions that may match a current block,and thus the quality of motion-compensated prediction usually improves,at least for some types of video content (e.g., natural video).

When MV precision is integer-sample precision for a unit of video, allMV values for blocks in the unit indicate integer-sample spatialdisplacements. When MV precision is a fractional-sample precision for aunit of video, an MV value for a block in the unit can indicate afractional-sample spatial displacement or an integer-sample spatialdisplacement. That is, when MV precision is a fractional-sampleprecision for a unit of video, some MV values for blocks in the unit canindicate fractional-sample spatial displacements, while other MV valuesfor blocks in the unit indicate integer-sample spatial displacements.

When encoding a block using motion estimation and motion compensation,an encoder often computes the sample-by-sample differences (also calledresidual values or error values) between the sample values of the blockand its motion-compensated prediction. The residual values may then beencoded. For the residual values, encoding efficiency depends on thecomplexity of the residual values and how much loss or distortion isintroduced as part of the compression process. In general, a goodmotion-compensated prediction closely approximates a block, such thatthe residual values are small-amplitude differences that can beefficiently encoded. On the other hand, a poor motion-compensatedprediction often yields residual values that include larger-amplitudevalues, which are more difficult to encode efficiently. Encoderstypically spend a large proportion of encoding time performing motionestimation, attempting to find good matches and thereby improverate-distortion performance.

When a codec uses MV values with integer-sample MV precision, an encoderand decoder need not perform interpolation operations between samplevalues of reference pictures for motion compensation, since the MVvalues indicate integer-sample spatial displacements. When a codec usesMV values with fractional-sample MV precision, an encoder and decodermay perform interpolation operations between sample values of referencepictures for motion compensation (adding computational complexity, atleast for MV values that indicate fractional-sample spatialdisplacements), but motion-compensated predictions tend to more closelyapproximate blocks (leading to residual values with fewer significantvalues), compared to integer-sample MV precision.

C. Representation of MV Values.

MV values are typically represented using integer values whose meaningdepends on an associated MV precision. For integer-sample MV precision,for example, an integer value of 1 indicates a spatial displacement of 1sample, an integer value of 2 indicates a spatial displacement of twosamples, and so on. For ¼-sample MV precision, for example, an integervalue of 1 indicates a spatial displacement of 0.25 samples. Integervalues of 2, 3, 4 and 5 indicate spatial displacements of 0.5, 0.75, 1.0and 1.25 samples, respectively. Regardless of MV precision, the integervalue can indicate a magnitude of the spatial displacement, and separateflag value can indicate whether displacement is negative or positive.The horizontal MV component and vertical MV component of a given MVvalue can be represented using two integer values. Thus, the meaning oftwo integer values representing an MV value depends on MV precision. Forexample, for an MV value having a 2-sample horizontal displacement andno vertical displacement, if MV precision is ¼-sample MV precision, theMV value is represented as (8, 0). If MV precision is integer-sample MVprecision, however, the MV value is represented as (2, 0).

MV values in a bitstream of encoded video data are typically entropycoded (e.g., on an MV-component-wise basis). An MV value may also bedifferentially encoded relative to a predicted MV value (e.g., on anMV-component-wise basis). In many cases, the MV value equals thepredicted MV value, so the differential MV value is zero, which can beencoded very efficiently. A differential MV value (or MV value, if MVprediction is not used) can be entropy encoded using Exponential-Golombcoding, context-adaptive binary arithmetic coding or another form ofentropy coding. Although the exact relationship between MV value (ordifferential MV value) and encoded bits depends on the form of entropycoding used, in general, smaller values are encoded more efficiently(that is, using fewer bits) because they are more common, and largervalues are encoded less efficiently (that is, using more bits) becausethey are less common.

D. Adaptive MV Precision—Introduction.

To summarize the preceding three sections, using MV values withinteger-sample MV precision tends to reduce bit rate associated withsignaling the MV values and reduce the computational complexity ofencoding and decoding (by avoiding interpolation of sample values atfractional-sample positions in reference pictures), but may reduce thequality of motion-compensated prediction and thus increase the amplitudeof the residual values, at least for some types of video content. On theother hand, using MV values with fractional-sample MV precision tends toincrease bit rate associated with signaling the MV values and increasethe computational complexity of encoding and decoding (by includinginterpolation of sample values at fractional-sample positions inreference pictures), but may improve the quality of motion-compensatedprediction and reduce the amplitude of the residual values, at least forsome types of video content. In general, the computational complexity,bit rate for signaling MV values, and quality of motion-compensatedprediction increase as MV precision increases (e.g., from integer-sampleto ½-sample, or from ½-sample to ¼-sample), up to a point of diminishingreturns. At the same time, although increased MV precision tends toincrease the bit rate needed to signal the MV values, when encodingnatural content the associated improvement in the quality ofmotion-compensated prediction may reduce the bit rate needed to send anadequate approximation of the residual values and thereby reduce thetotal bit rate needed to encode the video content with adequate picturequality.

When encoding screen capture video or other artificially-created videocontent, the added costs of fractional-sample MV precision (in terms ofbit rate and computational complexity) may be unjustified. For example,if most MV values represent integer-sample spatial displacements, andvery few MV values represent fractional-sample spatial displacements,the added costs of fractional-sample MV precision are not warranted. Theencoder can skip searching at fractional-sample positions (and skipinterpolation operations to determine sample values at fractional-samplepositions) during motion estimation. For such content, bit rate andcomputational complexity can be reduced, without a significant penaltyto the quality of motion-compensated prediction, by using MV values withinteger-sample MV precision.

Since fractional-sample MV precision may still be useful for other typesof video content (e.g., natural video captured by camera), an encoderand decoder can be adapted to switch between MV precisions. For example,an encoder and decoder can use integer-sample MV precision for screencapture video, but use a fractional-sample MV precision (such as¼-sample MV precision) for natural video. Approaches that an encoder mayfollow when selecting MV precision are described in the next section.The encoder can signal the selected MV precision to the decoder usingone or more syntax elements in the bitstream.

In one approach to signaling MV precision, when adaptive selection of MVprecision is enabled, the encoder selects an MV precision on aslice-by-slice basis. A flag value in a sequence parameter set (“SPS”),picture parameter set (“PPS”) or other syntax structure indicateswhether adaptive selection of MV precision is enabled. If so, one ormore syntax elements in a slice header for a given slice indicate theselected MV precision for blocks of that slice. For example, a flagvalue of 0 indicates ¼-sample MV precision, and a flag value of 1indicates integer-sample MV precision.

In another approach to signaling MV precision, the encoder selects an MVprecision on a picture-by-picture basis or slice-by-slice basis. Asyntax element in a PPS indicates one of three MV precision modes: (0)¼-sample MV precision for MV values of slice(s) of a picture associatedwith the PPS, (1) integer-sample MV precision for MV values of slice(s)of a picture associated with the PPS, or (2) slice-adaptive MV precisiondepending on a flag value signaled per slice header, where the flagvalue in the slice header of a slice can indicate ¼-sample MV precisionor integer-sample MV precision for MV values of the slice. Foradditional details about this approach in one implementation, seeJCTVC-P0277.

In still another approach to signaling MV precision, when adaptiveselection of MV precision is enabled, the encoder selects an MVprecision on a CU-by-CU basis. One or more syntax elements in astructure for a given CU indicate the selected MV precision for blocksof that CU. For example, a flag value in a CU syntax structure for a CUindicates whether MV values for all PUs associated with the CU haveinteger-sample MV precision or ¼-sample MV precision. For additionaldetails about this approach in one implementation, see JCTVC-P0283.

In any of these approaches, the encoder and decoder can use different MVprecisions for horizontal and vertical MV components. This can be usefulwhen encoding screen capture video that has been scaled horizontally orvertically (e.g., using integer-sample MV precision in an unscaleddimension, and using a fractional-sample MV precision in a scaleddimension). In some implementations, if rate control cannot be achievedsolely through adjustment of QP values, an encoder may resize screencapture video horizontally or vertically to reduce bit rate, then encodethe resized video. At the decoder side, the video is scaled back to itsoriginal dimensions after decoding. The encoder can signal the MVprecision for horizontal MV components (e.g., with a first flag value orsyntax element) and also signal the MV precision for vertical MVcomponents (e.g., with a second flag value or syntax element) to thedecoder.

More generally, when adaptive selection of MV precision is enabled, theencoder selects an MV precision and signals the selected MV precision insome way. For example, a flag value in a SPS, PPS or other syntaxstructure can indicate whether adaptive selection of MV precision isenabled. When adaptive MV precision is enabled, one or more syntaxelements in sequence-layer syntax, group-of-pictures-layer syntax(“GOP-layer syntax”), picture-layer syntax, slice-layer syntax,tile-layer syntax, block-layer syntax or another syntax structure canindicate the selected MV precision for MV values. Or, one or more syntaxelements in sequence-layer syntax, GOP-layer syntax, picture-layersyntax, slice-header-layer syntax, slice-data-layer syntax, tile-layersyntax, block-layer syntax or another syntax structure can indicate MVprecisions for different MV components. When there are two available MVprecisions, a flag value can indicate a selection between the two MVprecisions. Where there are more available MV precisions, an integervalue can indicate a selection between those MV precisions.

Aside from modifications to signal/parse the syntax elements thatindicate selected MV precision(s), decoding can be modified to changehow signaled MV values are interpreted depending on the selected MVprecision. The details of how MV values are encoded and reconstructedcan vary depending on MV precision. For example, when the MV precisionis integer-sample precision, predicted MV values can be rounded to thenearest integer, and differential MV values can indicate integer-sampleoffsets. Or, when the MV precision is ¼-sample precision, predicted MVvalues can be rounded to the nearest ¼-sample offset, and differentialMV values can indicate ¼-sample offsets. Or, MV values can be signaledin some other way. When MV values have integer-sample MV precision andthe video uses 4:2:2 or 4:2:0 chroma sampling, chroma MV values can bederived by scaling, etc., which may result in ½-sample displacements forchroma. Or, chroma MV values can be rounded to integer values.

E. Approaches to Selecting MV Precision.

When MV precision can be adapted during video encoding, an encoderselects an MV precision for a unit of video. The encoder can select theMV precision(s) to use based on hints from a video source (see approach1, below). For example, the video source can indicate that video isscreen capture content or natural video (captured from a camera). Or,the encoder can select the MV precision(s) based on exhaustiveevaluation of the various MV precisions (see approach 2, below). Or, theencoder can select the MV precision(s) based on analysis of statisticaldata from previous units and/or statistical data for the current unitbeing encoded (see approaches 3-4, below).

Some of the approaches to selecting MV precision are adapted to screencapture encoding scenarios. Other approaches more generally apply whenencoding any type of video content.

In some examples described in this section, the encoder selects betweenusing ¼-sample MV precision and integer-sample MV precision. Moregenerally, the encoder selects between multiple available MV precisions,which can include integer-sample MV precision, ½-sample MV precision,¼-sample MV precision and/or another MV precision.

When an encoder selects an MV precision for a unit of video, the unit ofvideo can be a sequence, GOP, picture, slice, tile, CU, PU, other blockor other type of unit of video. Depending on a desired tradeoff betweencomplexity and flexibility, selecting MV precision on a highly-localbasis (e.g., CU-by-CU basis), a larger region-by-region basis (e.g.,tile-by-tile basis or slice-by-slice basis), whole picture basis, ormore global basis (e.g., per encoding session, per sequence, per GOP, orper series of pictures between detected scene changes) may beappropriate.

1. Approaches that Use Hints from Application, Operating System or VideoSource.

An encoder can select MV precision based on a hint signaled by anapplication, operating system or video source. For example, the hint canindicate that the video content to be encoded was rendered by aparticular application, such as a word processor, spreadsheetapplication, or Web browser (without an embedded video region, which maybe natural video content). Rendering with such an application would tendto produce only integer-sample spatial displacements of the content.Based on such a hint, the encoder can select integer-sample MVprecision. For content rendered with a word processor, spreadsheetapplication, Web browser or other application that does not usuallyrender natural video content, integer-sample MV precision is likelypreferable to fractional-sample MV precision. (But fractional-sample MVprecision may be preferable if the video has been resized.)

Or, the hint can indicate that video content was delivered by a screencapture module or other video source that typically deliversartificially-created video content. For such content, integer-sample MVprecision is likely preferable to fractional-sample MV precision, so theencoder selects integer-sample MV precision. (But fractional-sample MVprecision may be preferable if the video has been resized.)

On the other hand, if the hint indicates video content was delivered bya camera, DVD or other disk, or tuner card, or rendered by a videoplayer, the encoder can select a fractional-sample MV precision. Forsuch content, fractional-sample MV precision is likely preferable tointeger-sample MV precision.

A hint can apply to an encoding session, to a series of frames, to asingle video frame or to part of a video frame (such as an areacorresponding to a window associated with an application).

In some cases, an encoder may not receive or may be unable to interpreta hint provided by a video source, operating system or applicationconcerning the nature of the video content. Or, the hint may beincorrect or misleading (e.g., for mixed-content video that includesnatural video content and artificially-created video content, or forvideo that has been resized). In such cases, the encoder can use anotherapproach to determine which MV precision(s) should be selected.

2. Brute-Force Encoding Approaches.

In another set of approaches to selecting MV precision, the encoderencodes a unit of video multiple times using different MV precisions(e.g., once with integer-sample MV precision, once with ¼-sample MVprecision). The encoder selects the MV precision that provides the bestperformance, and uses the selected MV precision when encoding the unitfor output. The unit of video can be a block, PU, CU, slice, tile,picture, GOP, sequence or other type of unit of video. Typically, theencoder performs multiple passes of encoding in such approaches.

To evaluate which MV precision provides the best performance, theencoder can determine rate-distortion cost when the different MVprecisions are used during encoding of the unit, and select the optionwith the lowest rate-distortion cost. A rate-distortion cost has adistortion cost D and a bit rate cost R, with a factor λ (often called aLagrangian multiplier) that weights the bit rate cost relative to thedistortion cost (D+λR) or vice versa (R+λD). The bit rate cost can be anestimated or actual bit rate cost. In general, the distortion cost isbased upon a comparison of original samples to reconstructed samples.The distortion cost can be measured as sum of absolute differences(“SAD”), sum of absolute Hadamard-transformed differences (“SAHD”) orother sum of absolute transformed differences (“SATD”), sum of squarederrors (“SSE”), mean squared error (“MSE”), mean variance or anotherdistortion metric. The factor λ can vary during encoding (e.g.,increasing the relative weight of the bit rate cost when quantizationstep size is larger). Rate-distortion cost usually provides the mostaccurate assessment of the performance of different MV precisionoptions, but also has the highest computational complexity.

The encoder can vary one or more of terms of the rate-distortion costfunction to bias the rate-distortion analysis towards the integer-sampleMV precision option. For example, when determining an MV precision for aunit of video using rate-distortion analysis to decide between multipleMV precisions, the rate-distortion analysis is biased towards theinteger-sample MV precision by scaling the distortion cost, adding apenalty to the distortion cost, scaling the bit rate cost, adding apenalty to the bit rate cost, and/or adjusting a Lagrangian multiplierfactor. When evaluating a fractional-sample MV precision, the encodercan scale up the distortion cost (by a factor greater than 1), scale upthe bit rate cost (by a factor greater than 1), add a distortionpenalty, add a bit rate penalty and/or use a larger Lagrangianmultiplier factor. Or, when evaluating the integer-sample MV precision,the encoder can scale down the distortion cost (by a factor less than1), scale down the bit rate cost (by a factor less than 1), and/or use asmaller Lagrangian multiplier factor.

The encoder can vary the extent of bias towards or againstinteger-sample MV precision during encoding. For example, the encodercan adjust bias towards integer-sample MV precision depending on adegree of confidence that integer-sample MV values are likely to be moreappropriate for encoding the video content (e.g., increasing biastowards integer-sample MV precision if the video content is likelyartificially-created content). Or, the encoder can adjust bias towardsinteger-sample MV precision depending on computational capacity forencoding and/or decoding (e.g., increasing bias towards integer-sampleMV precision if available computational capacity is lower).

Alternatively, the encoder can use another approach to evaluate which MVprecision provides the best performance. For example, the encodermeasures which MV precision results in the fewest bits of encoded data,for a given quantization step size. Or, the encoder evaluates onlydistortion for encoding that uses the different MV precisions. Or, theencoder uses a simpler measure such as distortion reduction benefit forfractional-sample MV precision compared to integer-sample MV precision,which may be simple enough to determine in a single pass of encoding.For example, the encoder examines the amount of distortion reduction (interms of SAD, SATD, TSE, MSE or another distortion metric) when afractional-sample MV precision is used, compared to when integer-sampleMV precision is used.

Brute-force encoding approaches can be computationally intensive. Theypotentially involve significant additional computations, additionalmemory storage, and additional memory read and write operations,compared to encoding that uses a fixed MV precision.

3. Approaches that Use Content Analysis.

In another set of approaches to selecting MV precision, an encoderselects the MV precision for a unit of video based on analysis of inputvideo content and/or encoded video content. The unit of video can be ablock, PB, PU, CU, CTU, sub-macroblock partition, macroblock, slice,tile, picture, GOP, sequence or other type of unit of video.

FIG. 8 shows a technique (800) for adapting MV precision duringencoding. The technique (800) can be performed by an encoder such as onedescribed with reference to FIG. 3 or FIGS. 4a and 4b , or by anotherencoder. According to the technique (800), during encoding of video, theencoder determines an MV precision from among multiple MV precisions forunits of the video. The multiple MV precisions can include one or morefractional-sample MV precisions as well as integer-sample MV precision.For example, the multiple MV precisions can include integer-sample MVprecision and ¼-sample MV precision. Or, the multiple MV precisions caninclude integer-sample MV precision, ½-sample MV precision and ¼-sampleMV precision.

Specifically, when encoding a unit of video, the encoder determines(810) whether to change MV precision. At the start of encoding, theencoder can initially set the MV precision according to a default value,or proceed as if changing the MV precision. For later units of video,the encoder may use the current MV precision (which was used for one ormore previously encoded units) or change the MV precision. For example,the encoder can decide to change MV precision upon the occurrence of adefined event (e.g., after encoding of a threshold-valued number ofunits, after a scene change, after a determination that the type ofvideo has changed).

To change the MV precision, the encoder collects (820) information aboutthe video. In general, the collected information can be characteristicsof input video or characteristics of encoded video. The collectedinformation can relate to the current unit being encoded and/or relateto previously encoded units of the video. (When the collectedinformation relates to one or more previously encoded units of thevideo, the collection (820) of such information can happen before,during or after the encoding of the previous unit(s). This collection(820) is different than the timing shown in FIG. 8, and happensregardless of the decision (810) about changing MV precision.) Theencoder then selects (830) MV precision for the unit of the video basedat least in part on the collected information.

As one example, the encoder can collect sample values for the currentunit. The presence of a small number of discrete sample values tends toindicate screen capture content, and hence suggest that integer-sampleMV precision should be selected. On the other hand, the presence of alarge number of discrete sample values tends to indicate natural video,and hence suggest that fractional-sample MV precision should beselected. The sample values can be organized as a histogram. Samplevalues can be collected from only luma (Y) samples in a YUV color space,from luma as well as chroma (U, V) samples in a YUV color space, from R,G and B samples in a RGB color space, or from only G (or R or B) samplesin a RGB color space. For example, when selecting the MV precision, theencoder determines a count of distinct sample values among the collectedsample values. The encoder compares the count to a threshold. If thecount is lower than the threshold, the encoder selects integer-sample MVprecision. If the count is higher than the threshold, the encoderselects a fractional-sample MV precision. The boundary condition (countequals threshold) can be handled using either option, depending onimplementation. Or, the encoder otherwise considers statistics from thecollected sample values. For example, the encoder determines whether thex most common collected sample values account for more than y % of thesample values. If so, the encoder selects integer-sample MV precision;otherwise, the encoder selects a fractional-sample MV precision. Thevalues of x and y depend on implementation. The value of x can be 10 orsome other count. The value of y can be 80, 90 or some other percentageless than 100.

As another example, the encoder can collect distortion measures forblocks of the current unit encoded with the respective MV precisions.For example, the encoder records improvement (reduction) in distortionwhen using fractional-sample MV precision, compared to integer-sample MVprecision. When selecting the MV precision, the encoder determineswhether a reduction in distortion justifies an increase in MV precision.

As another example, the encoder can collect MV values (having afractional-sample MV precision) for one or more previous units. Thecollected MV values can be organized according to value of theirfractional parts, e.g., for ¼-sample MV precision MV values, in ahistogram with a bin for MV values having fractional part of zero, a binfor MV values having fractional part of 0.25, a bin for MV values havinga fractional part of 0.5, and a bin for MV values having a fractionalpart of 0.75. Low-complexity variations of this approach are describedin the next section.

As another example, the encoder can collect information about count ofencoded bits for MV data (differential MV values) for blocks encodedusing a fractional-sample MV precision. A low average number of bits fordifferential MV values indicates regular (predictable) motion and ismore common when integer-sample MV precision would be appropriate. Ahigh average number of bits used for differential MV values is morecommon when fractional-sample MV precision would be appropriate. Whenselecting the MV precision, the encoder measures an average (or median)number of bits among the counts of encoded bits for differential MVvalues. The encoder compares the measure to a threshold. If the measureis lower than the threshold, the encoder selects integer-sample MVprecision. If the measure is higher than the threshold, the encoderselects a fractional-sample MV precision. The boundary condition(measure equals threshold) can be handled using either option, dependingon implementation.

As another example, when encoding a unit, the encoder evaluates themultiple MV precisions per block (e.g., PU) of the unit, and collectsinformation per block that indicates which MV precision provides thebest performance for that block. The encoder can determine therate-distortion cost (e.g., D+λR) when a block is encoded usinginteger-sample MV precision, and also determine the rate-distortion cost(e.g., D+λR) when the block is encoded using a fractional-sample MVprecision. The encoder determines how many times each of the multiple MVprecisions is best for the respective blocks within the unit, andselects the MV precision with the largest count. For example, for eachof the blocks in a picture, the encoder determines rate-distortion costwhen the block is encoded using integer-sample MV precision, and alsodetermines the rate-distortion cost when the block is encoded using¼-sample MV precision. The encoder counts the number of timesinteger-sample MV precision would be better and the number of times¼-sample MV precision would be better, then picks the higher of the two.Alternatively, the encoder determines a count of how many timesinteger-sample MV precision is best for the blocks of the unit, thenselects integer-sample MV precision only if the count is higher than athreshold percentage of the number of blocks in the unit. In someimplementations, the encoder considers blocks with any value of MV. Inother implementations, the encoder considers only blocks withnon-zero-value MVs. This block-wise evaluation of the multiple MVprecisions can be performed for blocks of a given unit in order toselect the MV precision for one or more subsequent units, regardless ofthe MV precision mode used for the given unit. Or, the block-wiseevaluation of the multiple MV precisions can be performed for a givenunit in order to select the MV precision for the given unit.

Alternatively, the encoder uses another approach to collectinginformation and selecting the MV precision based at least in part on theselected information.

Returning to FIG. 8, whether or not the MV precision has changed, theencoder encodes (840) the unit using the selected MV precision. MVvalues for blocks (e.g., PUs, macroblocks, or other blocks) within theunit of the video have the selected MV precision. The encoder outputsencoded data for the current unit, e.g., in a bitstream. The encodeddata can include syntax elements that indicate the selected MVprecision.

The encoder decides (850) whether to continue with the next unit. If so,the encoder decides (810) whether to change the MV precision for thenext unit. Thus, MV precision can be selected for each unit (e.g., persegment, per GOP, per picture, per slice, per CTU, per CU, per PU, perPB, per macroblock, per sub-macroblock partition). Or, to reducecomplexity, the MV precision for a unit can be changed from time-to-time(e.g., periodically or upon the occurrence of a defined event), thenrepeated for one or more subsequent units.

When the encoder uses the same pattern of tiles from picture-to-picture,the encoder can repeat per-tile MV precisions from picture-to-picture.Co-located tiles from picture-to-picture can use the same MV precision.Similarly, co-located slices from picture-to-picture can use the same MVprecision. For example, suppose video depicts a computer desktop, andpart of the desktop has a window displaying natural video content. Afractional-sample MV precision may be used within that region of thedesktop from picture-to-picture, whereas other areas that show text orother rendered content are encoded using integer-sample MV precision.

In this set of approaches, the encoder can use single-pass encoding. Forthe current unit of video being encoded, the selected MV precision forthe current unit depends at least in part on collected information fromone or more previous units of the video (in encoding order, which isalso called decoding order or bitstream order, not input order, which isalso called temporal order, output order or display order).

Alternatively, in this set of approaches, the encoder can use multi-passencoding or encoding with a short look-ahead window (sometimes called1.5-pass encoding). For the current unit of video being encoded, theselected MV precision depends at least in part on collected informationfrom the current unit. The selected MV precision for the current unitcan also depend at least in part on collected information from one ormore previous units of the video (in encoding order, not input order).

In this set of approaches, the encoder can adjust an amount of biastowards or against integer-sample MV precision based at least in part ona degree of confidence that integer-sample MV precision is appropriate.The encoder can also adjust an amount of bias towards or againstinteger-sample MV precision based at least in part on the computationalcapacity of encoding and/or decoding (favoring integer-sample MVprecision to reduce computational complexity if less computationalcapacity is available). For example, to favor selection ofinteger-sample MV precision, the encoder can adjust thresholds used incomparison operations to make it more likely that integer-sample MVprecision is selected.

In this set of approaches, the selected MV precision can be forhorizontal MV components and/or vertical MV components of the MV valuesfor blocks within the unit of the video, where the horizontal MVcomponents and vertical MV components are permitted to have different MVprecisions. Or, the selected MV precision can be for both horizontal MVcomponents and vertical MV components of the MV values for blocks withinthe unit of the video, where the horizontal MV components and verticalMV components have the same MV precision.

In this set of approaches, the encoded video (e.g., in the bitstream)includes one or more syntax elements that indicate the selected MVprecision for the unit. Alternatively, the encoded video can lack anysyntax elements that indicate the selected MV precision for the unit(see below, in the section about non-normative approaches). For example,even if the bitstream supports signaling of MV values with afractional-sample MV precision, the encoder can constrain motionestimation for the unit of the video to use only MV values withfractional parts of zero. This may reduce computational complexity ofencoding and decoding by avoiding interpolation operations.

4. Approaches that Use Low-Complexity Content Analysis.

To simplify the decision-making process, an encoder can consider asmaller set of data before selecting MV precision or use simplerdecision logic when selecting MV precision, avoiding multiple passes ofencoding.

FIG. 9 shows a technique (900) for adapting MV precision during encodingusing a low-complexity approach. The technique (900) can be performed byan encoder such as one described with reference to FIG. 3 or FIGS. 4aand 4b , or by another encoder. The technique (900) details one approachto collecting information about video and selecting MV precision basedat least in part on the collected information, as described withreference to FIG. 8.

According to the technique (900), during encoding of video, the encoderdetermines an MV precision for a unit of the video. When determining theMV precision for the unit, the encoder identifies (910) a set of MVvalues having a fractional-sample MV precision. The set of MV values canbe allowed to include zero-value MVs and non-zero-value MVs. Or, the setof MV values can be constrained to include only non-zero-value MVs. Or,the set of MV values can further be constrained to include onlynon-zero-value MVs from blocks of a certain block size or larger.

The encoder selects (920) the MV precision for the unit based at leastin part on prevalence, within the set of MV values, of MV values havinga fractional part of zero. The prevalence can be measured in terms ofthe fraction of the set of MV values having a fractional part of zero.For example, for a picture, the encoder can determine the percentage ofMV values having a fractional part of zero. Or, for a region or set ofregions that uses the set of MV values, the prevalence can be measuredin terms of the fraction of that region or set of regions having afractional part of zero. If the fraction exceeds a threshold, theselected MV precision for the unit is integer-sample MV precision. Ifthe fraction does not exceed the threshold, the selected MV precisionfor the unit is a fractional-sample MV precision. The boundary condition(the fraction equals threshold) can be handled using either option,depending on implementation.

The selection (920) of the MV precision for the unit can also be basedat least in part on prevalence of non-zero-value MVs, such thatswitching to integer-sample MV precision is permitted if there is athreshold amount of non-zero-value MVs. The prevalence of non-zero-valueMVs can be measured in terms of the fraction of MV values that arenon-zero-value MVs, in terms of count of blocks that use non-zero-valueMVs, or in terms of the fraction of a region or set of regions that usesnon-zero-value MVs. In this case, the set of MV values having afractional-sample MV precision can be identified from among non-zerovalue MVs of the region or set of regions. Thus, the encoder canconsider the prevalence of non-zero-value MVs having a fractional partof zero within the set of MVs that are non-zero-value MVs. For example,the encoder switches to integer-sample MV precision if two conditionsare satisfied: (1) a sufficiently large amount of non-zero-value MVs aredetected, and (2) within that set of non-zero-value MVs, there aresufficiently many that have a fractional part of zero (or,alternatively, sufficiently few that have a non-zero fractional part).The prevalence of non-zero-value MVs and the prevalence of MV valueshaving a fractional part of zero can be determined by counting MV values(regardless of their associated block size) or by considering theassociated block size for MV values (e.g., since some MV values areapplied to larger blocks than others).

The encoder encodes the unit using the selected MV precision for theunit. MV values for blocks (e.g., PUs, macroblocks, or other blocks)within the unit of the video have the selected MV precision for theunit. The encoder outputs encoded data for the current unit, e.g., in abitstream. The encoded data can include syntax elements that indicatethe selected MV precision for the unit.

To reduce the amount of time the encoder spends setting MV precision,after integer-sample MV precision is selected for a unit, the selectedMV precision can be used for subsequent units of the video until anevent causes the MV precision to switch back to a fractional-sample MVprecision. For example, the event can be encoding of a defined number ofunits, a scene change, or a determination, based on observations duringencoding, that switching back to the fractional-sample MV precisionwould be beneficial.

In one example implementation, the encoder encodes a unit of video(e.g., picture, tile, slice or CU) only once. To start, the encoderencodes a unit using ¼-sample MV precision. During encoding, the encoderdetermines whether fractional parts of MV values are zero or not. Forexample, the encoder measures what fraction of the MV values havenon-zero fractional parts. Or, since some MV values affect largerpicture regions than others, the encoder measures what fraction ofinter-picture predicted region(s) uses MV values with non-zerofractional parts (measuring area, not count of MV values). If thefraction exceeds a threshold (which depends on implementation and is,for example, 75%), the encoder switches to integer-sample MV precisionfor one or more subsequent units of the video.

In this example implementation, after the encoder switches tointeger-sample MV precision, the encoder can keep that integer-sample MVprecision indefinitely or until a defined event triggers a switch backto fractional-sample MV precision, at least temporarily. The event canbe, for example, encoding of a particular number of units (e.g., 100units). Or, the event can be a scene change. Or, the event can be adetermination, based on statistics collected while encoding, that aswitch back to fractional-sample MV precision is likely to bebeneficial. (Such statistics can be collected during encoding of somelimited amount area, to decide whether fractional-sample MV precisionwould have worked better for that area, then applied to switch MVprecision for one or more units.)

Whether video content is natural video content or artificially-createdvideo content, large portions of the video may be still. For example,the still portions could be stationary background in natural video orstationary content in screen capture content. Still portions of videohave zero-value MVs, which have fractional parts of zero when MVprecision is a fractional-sample MV precision. The presence of asignificant number of zero-value MVs can confound decision logic thatconsiders the fraction of MV values with non-zero fractional parts.

Therefore, the encoder can eliminate zero-value MVs from consideration.FIG. 10 shows a picture (1000) that includes a non-moving portion (1001)with (mostly) zero value MVs and two moving portions (1002, 1003) with(mostly) non-zero-value MVs. The encoder considers the non-zero-valueMVs in the moving portions (1002, 1003), but does not consider the MVvalues of the non-moving portion (1001). The encoder can switch tointeger-sample MV precision when the fraction of non-zero-value MVs (inthe moving portions (1002, 1003)) with fractional parts of zero exceedsa threshold (or when the fraction of the picture that uses non-zero MVswith fractional parts of zero (in terms of area) exceeds a threshold).

The encoder can also check that the number of non-zero-value MVs that isevaluated exceeds a threshold amount, so that decisions are not madebased on an insignificant number of MV values. This can make thedecision-making process more robust.

In another example implementation, the encoder encodes a given unit ofvideo (e.g., picture, tile, slice or CU) using ¼-sample MV precision.The encoder switches to integer-sample MV precision for one or moresubsequent units of the video if (1) more than x % of the unit usesinter-picture prediction with non-zero-value MVs, and (2) more than y %of the part of the unit that uses non-zero MVs has integer-value MVs(fractional parts of zero). The values of x and y depend onimplementation and can be, for example, 5 and 75, respectively.

In a similar example implementation, the encoder encodes a given unit ofvideo (e.g., picture, tile, slice or CU) using ¼-sample MV precision.The encoder switches to integer-sample MV precision for one or moresubsequent units of the video if (1) more than z PUs of the unit havenon-zero-value MVs, and (2) more than y % of those PUs haveinteger-value MVs (fractional parts of zero). The values of z and ydepend on implementation and can be, for example, 100 and 75,respectively.

MV values for larger regions may be more reliable than MV values forsmaller regions. The encoder can limit which MV values are evaluated.For example, the encoder can evaluate only MV values for blocks of acertain block size or larger (e.g., 16×16 or larger).

In another example implementation, the encoder encodes a given unit ofvideo (e.g., picture, tile, slice or CU) using ¼-sample MV precision.The encoder switches to integer-sample MV precision for one or moresubsequent units of the video if (1) more than z PUs of the unit are w×wor larger and have non-zero-value MVs, and (2) more than y % of thosePUs have integer-value MVs (fractional parts of zero). The values of w,z and y depend on implementation and can be, for example, 16, 100 and75, respectively.

5. Non-normative Approaches.

In most of the preceding examples, an encoder signals one or more syntaxelements indicating a selected MV precision in encoded data, e.g., inthe bitstream. A decoder parses the syntax element(s) indicating theselected MV precision and interprets MV values according to the selectedMV precision.

Alternatively, in a non-normative approach, the encoder does not signalany syntax elements indicating the MV precision selected by the encoder.For example, the encoder selects between integer-sample MV precision anda fractional-sample MV precision, but always encodes MV values at thefractional-sample MV precision. A decoder reconstructs and applies MVvalues at the fractional-sample MV precision.

When it selects integer-sample MV precision, the encoder can simplifymotion estimation by avoiding interpolation of sample values atfractional-sample offsets and by evaluating candidate prediction regionsonly at integer-sample offsets. Also, if MV prediction produces afractional value—e.g., using temporal MV prediction—the encoder canconsider only those MV differences that would result in integer valueswhen adding the MV difference to the fractional-valued MV prediction(e.g., from the temporal MV prediction). During decoding, motioncompensation can be simplified by avoiding interpolation of samplevalues at fractional-sample offsets.

Certain approaches described in the preceding section (e.g., using ascaled rate-distortion cost by scaling distortion cost and/or bit ratecost, or adding a distortion cost penalty or bit rate cost penalty, oradjusting the weight factor) can also be adapted for a non-normativeapproach. The encoder can vary the extent of bias towards or againstinteger-sample MV precision during encoding. Through the scaling,penalties and/or weight factor, the encoder can adjust bias towardsinteger-sample MV precision depending on a degree of confidence thatinteger-sample MV values are likely to be more appropriate for encodingthe video content, or depending on computational capacity for encodingor decoding.

6. Alternatives and Variations.

In some usage scenarios, the encoding order of pictures (also calleddecoding order or decoded order) differs from the temporal order atinput/camera-capture and display (also called display order). Theencoder can take such reordering into account when selecting MVprecision. For example, the encoder can select MV precision(s) based onthe temporal order of pictures rather than on the encoding order of thepictures.

In many of the examples described herein, intra BC prediction and motioncompensation are implemented in separate components or processes, and BVestimation and motion estimation are implemented in separate componentsor processes. Alternatively, intra BC prediction can be implemented as aspecial case of motion compensation, and BV estimation can beimplemented as a special case of motion estimation, for which thecurrent picture is used as a reference picture. In such implementations,a BV value can be signaled as an MV value but used for intra BCprediction (within the current picture) rather than inter-pictureprediction. As the term is used herein, “intra BC prediction” indicatesprediction within a current picture, whether that prediction is providedusing an intra-picture prediction module, a motion compensation module,or some other module. Similarly, a BV value can be represented using anMV value or using a distinct type of parameter or syntax element, and BVestimation can be provided using an intra-picture estimation module,motion estimation module or some other module. The approaches describedherein for selecting MV precision can be applied to determine theprecision of MV values that will be used as BV values for intra BCprediction (that is, with the current picture as reference picture).

VI. Innovative Features.

In addition to the claims presented below, innovative features describedherein include but are not limited to the following.

# Feature A1 A computing device comprising: means for encoding video,including means for determining a motion vector (“MV”) precision for aunit of the video, wherein MV values for blocks within the unit of thevideo have the MV precision for the unit, and wherein the means fordetermining the MV precision for the unit includes: means foridentifying a set of MV values having a fractional- sample MV precision;and means for selecting the MV precision for the unit based at least inpart on prevalence, within the set of MV values, of MV values having afractional part of zero; and means for outputting the encoded video. B1A computing device comprising: means for encoding video, including meansfor determining a motion vector (“MV”) precision for a unit of thevideo, wherein MV values for blocks within the unit of the video havethe MV precision for the unit, wherein the means for determiningincludes means for performing rate-distortion analysis to decide betweenmultiple MV precisions, the multiple MV precisions including one or morefractional-sample MV precisions and integer-sample MV precision, andwherein the rate-distortion analysis is biased towards theinteger-sample MV precision by: (a) scaling a distortion cost, (b)adding a penalty to the distortion cost, (c) scaling a bit rate cost,(d) adding a penalty to the bit rate cost, and/or (e) adjusting aLagrangian multiplier factor; and means for outputting the encoded videoC1 A computing device comprising: means for encoding video, includingmeans for determining a motion vector (“MV”) precision for a unit of thevideo from among multiple MV precisions, the multiple MV precisionsincluding one or more fractional-sample MV precisions and integer-sampleMV precision, wherein MV values for blocks within the unit of the videohave the MV precision for the unit, and wherein the means fordetermining includes: means for collecting information about the video;and means for selecting the MV precision for the unit based at least inpart on the collected information; and means for outputting the encodedvideo.

In view of the many possible embodiments to which the principles of thedisclosed invention may be applied, it should be recognized that theillustrated embodiments are only preferred examples of the invention andshould not be taken as limiting the scope of the invention. Rather, thescope of the invention is defined by the following claims. We thereforeclaim as our invention all that comes within the scope and spirit ofthese claims.

1.-20. (canceled)
 21. In a computer system, a method comprising:encoding frames of a video sequence, thereby producing encoded data,wherein the encoding the frames of the video sequence includes: encodingan indicator in a first-layer syntax structure that applies for at leastone of the frames of the video sequence, the indicator indicating:whether or not motion vector (“MV”) precision is adaptively selected forunits of the at least one of the frames; and if the MV precision for theunits of the at least one of the frames is not adaptively selected,whether the MV precision for the units of the at least one of the framesis fractional-sample precision or integer-sample precision; and if theMV precision for the units of the at least one of the frames isadaptively selected, for each of the units, setting a flag in asecond-layer syntax structure for the unit, the flag indicating whetherMV precision for the unit is fractional-sample precision orinteger-sample precision; and outputting the encoded data as part of abitstream, the encoded data including the encoded indicator in thefirst-layer syntax structure and, if the MV precision for the units ofthe at least one of the frames is adaptively selected, for each of theunits, the flag in the second-layer syntax structure for the unit thatindicates the MV precision for the unit.
 22. The method of claim 21,wherein the first-layer syntax structure is a sequence-layer syntaxstructure, wherein the units are frames, and wherein the second-layersyntax structure is a picture-layer syntax structure.
 23. The method ofclaim 21, wherein the first-layer syntax structure is a sequenceparameter set, wherein the units are slices, and wherein thesecond-layer syntax structure is a slice-header-layer syntax structure.24. The method of claim 21, wherein, for the indicator: a first possiblevalue indicates that the MV precision for the units of the at least oneof the frames is not adaptively selected and further indicates that theMV precision for the units of the at least one of the frames isfractional-sample precision; a second possible value indicates that theMV precision for the units of the at least one of the frames is notadaptively selected and further indicates that the MV precision for theunits of the at least one of the frames is integer-sample precision; anda third possible value indicates that the MV precision for the units ofthe at least one of the frames is adaptively selected.
 25. The method ofclaim 21, wherein, for a given unit of the units, if the flag for thegiven unit is not present in the bitstream, the flag for the given unitis inferred to have a value equal to the indicator.
 26. The method ofclaim 21, wherein the encoding the indicator uses two bits in thefirst-layer syntax structure.
 27. The method of claim 21, wherein theencoding the indicator includes entropy coding a two-bit value for thefirst-layer syntax structure.
 28. The method of claim 21, wherein thefractional-sample precision is quarter-sample precision.
 29. The methodof claim 21, wherein the indicator is based on source of the frames ofthe video sequence, measurement of a performance heuristic, orhistorical data.
 30. A computer system comprising memory and one or moreprocessing units, wherein the computer system implements a video decoderconfigured to perform operations comprising: receiving encoded data forframes of a video sequence as part of a bitstream; and decoding theencoded data to reconstruct the frames of the video sequence, including:determining an indicator using a first-layer syntax structure thatapplies for at least one of the frames of the video sequence, theindicator indicating: whether or not motion vector (“MV”) precision isadaptively selected for units of the at least one of the frames; and ifthe MV precision for the units of the at least one of the frames is notadaptively selected, whether the MV precision for the units of the atleast one of the frames is fractional-sample precision or integer-sampleprecision; determining, based on the indicator, whether or not the MVprecision for the units of the at least one of the frames is adaptivelyselected; if the MV precision for the units of the at least one of theframes is not adaptively selected, for each of the units, determining,based on the indicator, whether MV precision for the unit isfractional-sample precision or integer-sample precision; and if the MVprecision for the units of the at least one of the frames is adaptivelyselected, for each of the units, determining, based on a flag in asecond-layer syntax structure for the unit, whether the MV precision forthe unit is fractional-sample precision or integer-sample precision. 31.The computer system of claim 30, wherein the first-layer syntaxstructure is a sequence-layer syntax structure, wherein the units areframes, and wherein the second-layer syntax structure is a picture-layersyntax structure.
 32. The computer system of claim 30, wherein thefirst-layer syntax structure is a sequence parameter set, wherein theunits are slices, and wherein the second-layer syntax structure is aslice-header-layer syntax structure.
 33. The computer system of claim30, wherein, for the indicator: a first possible value indicates thatthe MV precision for the units of the at least one of the frames is notadaptively selected and further indicates that the MV precision for theunits of the at least one of the frames is fractional-sample precision;a second possible value indicates that the MV precision for the units ofthe at least one of the frames is not adaptively selected and furtherindicates that the MV precision for the units of the at least one of theframes is integer-sample precision; and a third possible value indicatesthat the MV precision for the units of the at least one of the frames isadaptively selected.
 34. The computer system of claim 30, wherein, for agiven unit of the units, if the flag for the given unit is not presentin the bitstream, the flag for the given unit is inferred to have avalue equal to the indicator.
 35. The computer system of claim 30,wherein the determining the indicator uses two bits from the first-layersyntax structure.
 36. The computer system of claim 30, wherein thedetermining the indicator includes entropy decoding an entropy-codedtwo-bit value from the first-layer syntax structure.
 37. The computersystem of claim 30, wherein the fractional-sample precision isquarter-sample precision.
 38. One or more non-volatile memory or storagedevices having stored therein encoded data for frames of a videosequence as part of a bitstream, the encoded data including: anindicator, encoded in a first-layer syntax structure that applies for atleast one of the frames of the video sequence, indicating: whether ornot motion vector (“MV”) precision is adaptively selected for units ofthe at least one of the frames; and if the MV precision for the units ofthe at least one of the frames is not adaptively selected, whether theMV precision for the units of the at least one of the frames isfractional-sample precision or integer-sample precision; and if the MVprecision for the units of the at least one of the frames is adaptivelyselected, for each of the units, a flag in a second-layer syntaxstructure for the unit, the flag indicating whether MV precision for theunit is fractional-sample precision or integer-sample precision; whereinthe encoded data results from encoding of the frames of the videosequence according to operations comprising: determining whether or notthe MV precision for the units of the at least one of the frames isadaptively selected; if the MV precision for the units of the at leastone of the frames is not adaptively selected, for each of the units,determining whether the MV precision for the unit is fractional-sampleprecision or integer-sample precision; encoding the indicator in thefirst-layer syntax structure; and if the MV precision for the units ofthe at least one of the frames is adaptively selected, for each of theunits: determining whether the MV precision for the unit isfractional-sample precision or integer-sample precision; and setting theflag in the second-layer syntax structure for the unit.
 39. The one ormore non-volatile memory or storage devices of claim 38, wherein thefirst-layer syntax structure is a sequence-layer syntax structure,wherein the units are frames, and wherein the second-layer syntaxstructure is a picture-layer syntax structure.
 40. The one or morenon-volatile memory or storage devices of claim 38, wherein thefirst-layer syntax structure is a sequence parameter set, wherein theunits are slices, and wherein the second-layer syntax structure is aslice-header-layer syntax structure.